Detecting Noncompliance

Cognitive map for detecting 80 fraud situations. CRex uses rules-based, and probabilistic Bayesian situation assessors for fraud identification, unifying both within a single holistic fraud model, combining available data and expert knowledge within a master model for explainable fraud detection. Above, the CRex dashboard explaining impacts of identified fraudulent situations

Fraud detection requires processing vast amounts of data to uncover noncompliant transactions, with reporting that is verifiable and explainable according to applicable regulations and laws. Further, the community of taxpayers is continually evolving, with dynamic and novel evasion strategies constantly emerging.

CRex cognitive mapping uniquely partners human analysts and auditors with XAI to:

  • Identify potential fraud and compliance situations
  • Assess how they impact tax authority goals
  • Provide explanations behind its findings for more efficient review in the field